A SQLite-backed minimalistic knowledge based for robotic application. Mostly KB-API conformant.
Project description
minimalKB is a SQLite-backed minimalistic knowledge base, initially designed for robots (in particular human-robot interaction or multi-robot interaction).
It stores triples (like RDF/OWL triples), and provides a mostly conformant KB-API API accessible via a simple socket protocol.
pykb provides an idiomatic Python binding, making easy to integrate the knowledge base in your applications.
It has almost no features, except it is fast and simple. Basic RDFS reasoning is provided (cf below for details).
Written in Python. The only required dependency is sqlite3. If rdflib is also available, you can easily import existing ontologies in RDF/OWL/n3/Turtle formats in the knowledge base.
Installation
$ git clone https://github.com/severin-lemaignan/minimalkb.git $ cd minimalkb $ python setup.py install $ minimalkb
Run minimalkb --help for available options.
Features
Multi-models
The minimalKB is intended for dynamic environments, with possibly several contexts/agents requiring separate knowledge models.
New models can be created at any time and each operation (like knowledge addition/retractation/query) can operate on a specific subset of models.
Reasoning
minimalKB only provides basic RDFS reasoning capabilities: it honors the transitive closure of the rdfs:subClassOf relation.
The reasoner runs in its own thread, and classify the model at a given rate, by default 5Hz. It is thus needed to wait ~200ms before the results of the classification become visible in the model.
Transient knowledge
minimalKB allows to attach ‘lifespans’ to statements: after a given duration, they are automatically collected.
Ontology walking
minimalKB exposes several methods to explore the different ontological models of the knowledge base. It is compatible with the visualization tool oro-view.
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